Using Maximum Simulated Likelihood Methods to Overcome Left Censoring: Dynamic Event History Models of Heart Attack Risk in New Zealand

Autor:	Tue Gørgens, Sanghyeok Lee
Rok vydání:	2021
Předmět:	Statistics and Probability Economics and Econometrics business.industry Censoring (clinical trials) Statistics Event history Medicine Statistics Probability and Uncertainty business Social Sciences (miscellaneous)
Zdroj:	Journal of the Royal Statistical Society Series A: Statistics in Society. 185:348-376
ISSN:	1467-985X 0964-1998
Popis:	This paper describes how the risk of experiencing heart attacks varies across gender and ethnicity in New Zealand. We estimate dynamic hazard models using administrative data. We deal with left-censored data using recently developed maximum simulated likelihood methods. The models allow risk to vary with age, previous heart attack history and unobserved individual heterogeneity. We find that the risk of subsequent events is far higher than the risk of the first event, particularly high within 1 year after an event, and that unobserved heterogeneity is important. Generally, male Maoris have the highest risk, followed by female Maoris, then ethnically European males, while ethnically European females have the lowest risk.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c1068613a0d62d5bff76f37c8a7852f1 https://doi.org/10.1111/rssa.12758 Zobrazit plný text záznamu Plný text